Image Object Detection Model for Random Sample Images Using TensorFlow Take 5

David Lowe

November 5, 2021

Template Credit: Adapted from an Object Detection tutorial on TensorFlow.org.

Additional Notes: I adapted this workflow from the TensorFlow Object Detection tutorial on TensorFlow.org (https://www.tensorflow.org/hub/tutorials/object_detection). I plan to build a script for building future projects using object detection models.

SUMMARY: This project aims to construct an object detection model using the TensorFlow-based neural network and document the end-to-end steps using a template.

This iteration will use the TF2 Mask R-CNN Inception ResNet V2 1024x1024 object detection model to test some sample images. The model was constructed using the Mask R-CNN Object detection model and trained on COCO 2017 dataset with training images scaled to 1024x1024.

Original Script Location: https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/tf2_object_detection.ipynb

Images Used: See project code below

Dataset ML Model: Image Object Detection using TensorFlow Hub Models

Additional References: https://tfhub.dev/s?module-type=image-object-detection

Task 1 - Prepare Environment

Task 2 - Set up Visualization and Helper Functions

Task 3 - Prepare and Load Model

Task 4 - Load Images and Apply Model